As consumer demand for high data rate applications, such as streaming video, expands, technology providers are forced to adopt new technologies to provide the necessary bandwidth. Multiple-input Multiple-Output (“MIMO”) is an advanced radio system that employs multiple transmit antennas and multiple receive antennas to simultaneously transmit multiple parallel data streams. Relative to previous wireless technologies, MIMO enables substantial gains in both system capacity and transmission reliability without requiring an increase in frequency resources.
MIMO systems exploit differences in the paths between transmit and receive antennas to increase data throughput and diversity. As the number of transmit and receive antennas is increased, the capacity of a MIMO channel increases linearly, and the probability of all sub-channels between the transmitter and receiver fading simultaneously decreases exponentially. As might be expected, however, there is a price associated with realization of these benefits. Recovery of transmitted information in a MIMO system becomes increasingly complex with the addition of transmit antennas.
Many MIMO detection algorithms have been proposed. The maximum-likelihood detector, while conceptually simple and exhibiting optimal detection performance, is often impractical because its complexity increases exponentially with the number of input channels and constellation size. Consequently, a vast assortment of algorithms have been proposed to solve the detection problem with reduced complexity while sacrificing minimal performance. Many MIMO detectors have been proposed exclusively as hard detectors that give only the final estimate of the channel input. Most notable is the sphere detector because it can achieve near maximum-likelihood performance in an uncoded system with much less complexity on average. A summary of many other previously proposed MIMO detectors is given in Deric W. Waters, Signal Detection Strategies and Algorithms for Multiple-input Multiple-Output Channels (December 2005) (unpublished Ph.D. dissertation, Georgia Institute of Technology), http://etd.gatech.edu, including many variations of the sphere detector that have been proposed to minimize complexity without sacrificing performance. In Bernard M. Hochwald & Stephan ten Brink, Achieving Near-Capacity on a Multiple-Antenna Channel, 51 IEEE TRANSACTIONS ON COMMUNICATIONS 389-99 (2003), the list-sphere detector was proposed as a way to compute the log-likelihood ratio (LLR) for the channel input. There is an ongoing need to design wireless signal detectors with low complexity and good performance.